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Dany LauzonDepartment of Civil, Geological and Mining Engineering
Profile in the Directory of Experts of Polytechnique Montréal
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Arega, K. A., Benoit, N., & Lauzon, D. (2026, May). Stochastic groundwater recharge modelling in the Harricana river watershed, Québec, Canada [Poster]. CGU and IAH-CNC Annual Meeting 2026, Halifax, Nova Scotia. External link
Brisebois, O., Lauzon, D., & Pasquier, P. (2026, May). Investigation of a constructive geostatistical method to assimilate unused conventional data during geothermal drilling for hydraulic conductivity profiling [Paper]. 15th IEA Heat Pump Conference (HPC 2026), Vienna, Austria (12 pages). External link
Dion, G., Pasquier, P., & Lauzon, D. (2026, May). Stochastic approach to ground heat exchanger sizing accounting for weather and ground property variability [Paper]. 15th IEA Heat Pump Conference (HPC 2026), Vienna, Austria (10 pages). External link
Hoerning, S., Lauzon, D., & Bárdossy, A. (2025, April). Spectral methods for non-linear co-regionalization [Abstract]. EGU General Assembly 2025, Vienna, Austria (1 page). Available
Kfoury, M., Roy, S., Langevin, M., Lauzon, D., & Gosselin, Y. (2024, September). Geostatistical analysis of geotechnical uncertainty: risk assessment in engineering projects [Paper]. 77th Canadian Geotechnical Conference and the 16th Joint CGS/IAH-CNC Groundwater Conference (GeoMontréal 2024), Montreal, Quebec, Canada (7 pages). Available
Lauzon, D., Hörning, S., & Bàrdossy, A. (2026). A generalized FFTMA approach for simulating multivariate non-Gaussian random fields with spatial asymmetry. Computers & Geosciences, 212, 106157 (18 pages). External link
Lauzon, D. (2026). Géostatistique et géologie minière [Lecture Notes]. External link
Lauzon, D., Straubhaar, J., & Renard, P. (2025). A Deep Generative Model for the Simulation of Discrete Karst Networks. Earth and Space Science, 12(10). External link
Liang, X. X., Gloaguen, E., Claprood, M., Paradis, D., & Lauzon, D. (2025). Graph Neural Network Framework for Spatiotemporal Groundwater Level Forecasting. Mathematical Geosciences, 23 pages. External link
Lauzon, D., Hörning, S., & Bárdossy, A. (2025, April). A novel framework for stochastic simulation of multivariate non-gaussian random fields in environmental and geological studies [Abstract]. EGU General Assembly 2025, Vienna, Austria (2 pages). Available
Lauzon, D., & Hörning, S. (2025). Efficient computation on large regular grids of higher-order spatial statistics via fast fourier transform. Computers & Geosciences, 105878 (38 pages). External link
Lauzon, D., Tahan, S.-A., Agard, B., & Gamache, M. (2025, May). Analyse technique et économique des équipements miniers souterrains : étude de cas [Poster]. 92e congrès de l’ACFAS, Montréal, QC, Canada. External link
Lauzon, D., & Gloaguen, E. (2024). Quantifying uncertainty and improving prospectivity mapping in mineral belts using transfer learning and Random Forest: A case study of copper mineralization in the Superior Craton Province, Quebec, Canada. Ore Geology Reviews, 166, 105918 (16 pages). Available
Lauzon, D. (2024, June). Deep neural networks in surrogate hydrogeological modeling : an application for transient groundwater flow combined with a geostatistical spectral algorithm for inverse problem-solving [Abstract]. 15th International Conference on Geostatistics for Environmental Applications (GeoEnv 2024), Chania, Greece. Available
Lauzon, D. (2024). A U-Net architecture as a surrogate model combined with a geostatistical spectral algorithm for transient groundwater flow inverse problems. Advances in Water Resources, 189, 104726 (14 pages). External link
Lauzon, D., & Marcotte, D. (2023). Joint hydrofacies-hydraulic conductivity modeling based on a constructive spectral algorithm constrained by transient head data. Hydrogeology Journal, 31(6), 1647-1664. External link
Lauzon, D. (2022). Développement d'algorithmes pour le calage de modèles géologiques par méthodes géostatistiques discrètes et spectrales [Ph.D. thesis, Polytechnique Montréal]. Available
Lauzon, D., & Marcotte, D. (2022, June). On a constructive spectral method for conditioning pluriGaussian simulations to boreholes observations and indirect data. Application to aquifer models [Poster]. 14th International Conference on Geostatistics for Environmental Applications (GeoEnv 2022), Parma, Italia (1 page). External link
Lauzon, D., & Marcotte, D. (2022, June). On a constructive spectral method for conditioning pluriGaussian simulations to boreholes observations and indirect data. Application to aquifer models [Paper]. 14th International Conference on Geostatistics for Environmental Applications (GeoEnv 2022), Parma, Italia. External link
Lauzon, D., & Marcotte, D. (2022). Statistical comparison of variogram-based inversion methods for to indirect data. Computers & Geosciences, 160, 105032 (15 pages). External link
Lauzon, D., & Marcotte, D. (2020). Calibration of random fields by a sequential spectral turning bands method. Computers and Geosciences, 135, 13 pages. External link
Lauzon, D., & Marcotte, D. (2020). The sequential spectral turning band simulator as an alternative to Gibbs sampler in large truncated- or pluri- Gaussian simulations. Stochastic Environmental Research and Risk Assessment, 34(11), 1939-1951. External link
Lauzon, D., & Marcotte, D. (2019). Calibration of random fields by FFTMA-SA. Computers & Geosciences, 127, 99-110. External link
Pugliese, E., Lauzon, D., Dematteis, A., Rodani, S., Benedetti, G., & Gargini, A. (2026). Risk assessment of tunnelling-induced hydrogeological interference on springs using a machine learning approach. Hydrogeology Journal, 29 pages. Available
Paula Burgoa Tanaka, A., Renard, P., Xia Liang, X., Straubhaar, J., & Lauzon, D. (2026, May). Fracture network modeling with graph deep learning [Abstract]. EGU General Assembly 2026, Vienna, Austria. External link
Renard, P., Straubhaar, J., Lauzon, D., & Trunz, C. (2026, May). Karst network simulation with statistical learning [Abstract]. EGU General Assembly 2026, Vienna, Austria. External link
Straubhaar, J., Lauzon, D., & Renard, P. (2024, July). Graph recurrent neural networks for stochastic simulation of Karst network topology and properties [Abstract]. 15th International Conference on Geostatistics for Environmental Applications (GeoEnv 2024), Chania, Greece. External link
